Text cleaning pipeline in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert all text in the list to lowercase.

Data Analysis Python

texts = ['Hello World', 'Data Science']
lower_texts = [text.[1]() for text in texts]
print(lower_texts)

Drag options to blanks, or click blank then click option'

Aupper

Blower

Ctitle

Dcapitalize

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'upper()' instead of 'lower()' changes text to uppercase.

Using 'capitalize()' only changes the first letter.

The lower() method converts all characters in a string to lowercase.

2fill in blank

medium

Complete the code to remove leading and trailing spaces from each string.

Data Analysis Python

texts = ['  data ', ' science  ']
clean_texts = [text.[1]() for text in texts]
print(clean_texts)

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Ajoin

Bsplit

Creplace

Dstrip

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'split()' splits the string into words, not removing spaces.

Using 'replace()' needs extra arguments to remove spaces.

The strip() method removes spaces from the start and end of a string.

3fill in blank

hard

Fix the error in the code to remove punctuation from the text using string.punctuation.

Data Analysis Python

import string
text = 'Hello, world!'
clean_text = ''.join(char for char in text if char not in [1])
print(clean_text)

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Astring.punct

Bstring.punctuations

Cstring.punctuation

Dpunctuation.string

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'string.punct' which does not exist.

Swapping the order like 'punctuation.string' which is invalid.

The correct attribute for all punctuation characters is string.punctuation.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

Data Analysis Python

words = ['data', 'is', 'fun', 'science']
lengths = {word: [1] for word in words if [2]
print(lengths)

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Comparing the word string directly to a number.

The dictionary comprehension maps each word to its length using len(word). The condition keeps words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 4 characters.

Data Analysis Python

words = ['hello', 'data', 'science', 'fun']
result = { [1]: [2] for w in words if [3] }
print(result)

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Aw.upper()

Blen(w)

Clen(w) > 4

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase for keys.

Not filtering words by length.

The dictionary comprehension uses w.upper() as keys, len(w) as values, and filters words with length greater than 4.